S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Stochastic Dynamic Northern Corn Rootworm Population Model, January 2000

A complete life cycle model for northern corn rootworm, Diabrotica barberi Smith and Lawrence, is developed using a published single-season model of adult population dynamics and data from field experiments. Temperature-dependent development and age-dependent advancement determine adult population dynamics and oviposition, while a simple stochastic hatch and density-dependent larval survival model determine adult emergence. Dispersal is not modeled. To evaluate the long-run performance of the model, stochastically generated daily air and soil temperatures are used for 100-year simulations for a variety of corn planting and flowering dates in Ithaca, NY, and Brookings, SD. Once the model is corrected for a bias in oviposition, model predictions for both locations are consistent with anecdotal field data. Extinctions still occur, but these may be consistent with northern corn rootworm metapopulation dynamics.

Rates of cultural change and patterns of cultural accumulation in stochastic models of social transmission.

Cultural variation in a population is affected by the rate of occurrence of cultural innovations, whether such innovations are preferred or eschewed, how they are transmitted between individuals in the population, and the size of the population. An innovation, such as a modification in an attribute of a handaxe, may be lost or may become a property of all handaxes, which we call "fixation of the innovation." Alternatively, several innovations may attain appreciable frequencies, in which case properties of the frequency distribution-for example, of handaxe measurements-is important. Here we apply the Moran model from the stochastic theory of population genetics to study the evolution of cultural innovations. We obtain the probability that an initially rare innovation becomes fixed, and the expected time this takes. When variation in cultural traits is due to recurrent innovation, copy error, and sampling from generation to generation, we describe properties of this variation, such as the level of heterogeneity expected in the population. For all of these, we determine the effect of the mode of social transmission: conformist, where there is a tendency for each naïve newborn to copy the most popular variant; pro-novelty bias, where the newborn prefers a specific variant if it exists among those it samples; one-to-many transmission, where the variant one individual carries is copied by all newborns while that individual remains alive. We compare our findings with those predicted by prevailing theories for rates of cultural change and the distribution of cultural variation.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Limits on the validity of infinite length assumptions for modelling shallow landslides

The infinite slope method is widely used as the geotechnical component of geomorphic and landscape evolution models. Its assumption that shallow landslides are infinitely long (in a downslope direction) is usually considered valid for natural landslides on the basis that they are generally long relative to their depth. However, this is rarely justified, because the critical length/depth (L/H) ratio below which edge effects become important is unknown. We establish this critical L/H ratio by benchmarking infinite slope stability predictions against finite element predictions for a set of synthetic two-dimensional slopes, assuming that the difference between the predictions is due to error in the infinite slope method. We test the infinite slope method for six different L/H ratios to find the critical ratio at which its predictions fall within 5% of those from the finite element method. We repeat these tests for 5000 synthetic slopes with a range of failure plane depths, pore water pressures, friction angles, soil cohesions, soil unit weights and slope angles characteristic of natural slopes. We find that: (1) infinite slope stability predictions are consistently too conservative for small L/H ratios; (2) the predictions always converge to within 5% of the finite element benchmarks by a L/H ratio of 25 (i.e. the infinite slope assumption is reasonable for landslides 25 times longer than they are deep); but (3) they can converge at much lower ratios depending on slope properties, particularly for low cohesion soils. The implication for catchment scale stability models is that the infinite length assumption is reasonable if their grid resolution is coarse (e.g. >25?m). However, it may also be valid even at much finer grid resolutions (e.g. 1?m), because spatial organization in the predicted pore water pressure field reduces the probability of short landslides and minimizes the risk that predicted landslides will have L/H ratios less than 25. Copyright (c) 2012 John Wiley & Sons, Ltd.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Bioclimatic constraints to Andean cat distribution: a modelling application for rare species

AimTo identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model.LocationSouth America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina.MethodsWe used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data.ResultsSimple bioclimatic models for Andean cats were highly predictive with only 3-4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions.Main conclusionsSimple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.

Modelling the effect of minor orthopaedic day surgery on patient mood at the early post-operative period: a prospective population-based cohort study.

OBJECTIVE: The effect of minor orthopaedic day surgery (MiODS) on patient's mood. METHODS: A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study - Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively. RESULTS: The mean physical component score of SF-36 before surgery was 45.3 (SD=+/-10.1) and 8 weeks following surgery was 44.9 (SD=+/-11.04) [n=148, p=0.51, 95% CI=(-1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov=69.44) corresponded to a correlation coefficient, r=0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with chi(2) (df=1)=0.86 for which p=0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected. CONCLUSIONS: MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.

Stochastic dominance and absolute risk aversion

In this paper we proose the infimum of the Arrow-Pratt index of absoluterisk aversion as a measure of global risk aversion of a utility function.We then show that, for any given arbitrary pair of distributions, thereexists a threshold level of global risk aversion such that all increasingconcave utility functions with at least as much global risk aversion wouldrank the two distributions in the same way. Furthermore, this thresholdlevel is sharp in the sense that, for any lower level of global riskaversion, we can find two utility functions in this class yielding oppositepreference relations for the two distributions.

The achievable region approach to the optimal control of stochastic systems

The achievable region approach seeks solutions to stochastic optimisation problems by: (i) characterising the space of all possible performances(the achievable region) of the system of interest, and (ii) optimisingthe overall system-wide performance objective over this space. This isradically different from conventional formulations based on dynamicprogramming. The approach is explained with reference to a simpletwo-class queueing system. Powerful new methodologies due to the authorsand co-workers are deployed to analyse a general multiclass queueingsystem with parallel servers and then to develop an approach to optimalload distribution across a network of interconnected stations. Finally,the approach is used for the first time to analyse a class of intensitycontrol problems.

Multiscale phylogeography: glacial history and autopolyploidy of Biscutella laevigata L. (Brassicaceae) in the Western Alps

Résumé Les changements climatiques du Quaternaire ont eu une influence majeure sur la distribution et l'évolution des biota septentrionaux. Les Alpes offrent un cadre spatio-temporel bien étudié pour comprendre la réactivité de la flore et le potentiel d'adaptation d'une espèce végétale face aux changements climatiques. Certaines hypothèses postulent une diversification des espèces en raison de la disparition complète de la flore des Alpes et d'un isolement important des espèces dans des refuges méridionaux durant les dernières glaciations (Tabula Rasa). Une autre hypothèse stipule le maintien de poches de résistance pour la végétation au coeur des Alpes (Nunataks). Comme de nombreuses espèces végétales présentant un grand succès écologique semblent avoir réagi aux glaciations par la multiplication de leur génome (autopolyploïdie), leur étude en milieu naturel devrait permettre de comprendre les avantages inhérents à la polyploïdie. Biscutella laevigata est un modèle emblématique de biogéographie historique, diverses études ayant montré que des populations diploïdes sont actuellement isolées dans les zones restées déglacées durant le dernier maximum glaciaire, alors que des tétraploïdes ont recolonisé l'ensemble des zones alpines mises à nu par le retrait des glaciers. Si le contexte périglaciaire semble avoir favorisé ce jeune complexe autopolyploïde, les circonstances et les avantages de cette mutation génomique ne sont pas encore clairs. Y a-t-il eu de multiples événements de polyploïdisation ? Dans quelle mesure affecte(nt)il(s) la diversité génétique et le potentiel évolutif des polyploïdes ? Les polyploïdes ont-ils une grande flexibilité génomique, favorisant une radiation adaptative, ou doivent-ils leur succès à une grande plasticité écologique ? Cette étude aborde ces questions à différentes échelles spatiales et temporelles. L'échelle régionale des Alpes occidentales permet d'aborder les facteurs distaux (aspects historiques), alors que l'échelle locale cherche à appréhender les facteurs proximaux (mécanismes évolutifs). Dans les Alpes occidentales, des populations ont été densément échantillonnées et étudiées grâce à (1) leur cytotype, (2) leur appartenance taxonomique, (3) leur habitat et (4) des marqueurs moléculaires de l'ADN chloroplastique, en vue d'établir leurs affinités évolutives. Á l'échelle locale, deux systèmes de population ont été étudiés : l'un où les populations persistent en périphérie de l'aire de distribution et l'autre au niveau du front actif de colonisation, en marge altitudinale. Les résultats à l'échelle des Alpes occidentales révèlent les sites d'intérêt (refuges glaciaires, principales barrières et voies de recolonisation) pour une espèce représentative des pelouses alpines, ainsi que pour la biodiversité régionale. Les Préalpes ont joué un rôle important dans le maintien de populations à proximité immédiate des Alpes centrales et dans l'évolution du taxon, voire de la végétation. Il est aussi démontré que l'époque glaciaire a favorisé l'autopolyploïdie polytopique et la recolonisation des Alpes occidentales par des lignées distinctes qui s'hybrident au centre des Alpes, influençant fortement leur diversité génétique et leur potentiel évolutif. L'analyse de populations locales en situations contrastées à l'aide de marqueurs AFLP montre qu'au sein d'une lignée présentant une grande expansion, la diversité génétique est façonnée par des forces évolutives différentes selon le contexte écologique et historique. Les populations persistant présentent une dispersion des gènes restreinte, engendrant une diversité génétique assez faible, mais semblent adaptées aux conditions locales de l'environnement. À l'inverse, les populations colonisant la marge altitudinale sont influencées par les effets de fondation conjugués à une importante dispersion des gènes et, si ces processus impliquent une grande diversité génétique, ils engendrent une répartition aléatoire des génotypes dans l'environnement. Les autopolyploïdes apparaissent ainsi comme capables de persister face aux changements climatiques grâce à certaines facultés d'adaptation locale et de grandes capacités à maintenir une importante diversité génétique lors de la recolonisation post-glaciaire. Summary The extreme climate changes of the Quaternary have had a major influence on species distribution and evolution. The European Alps offer a great framework to investigate flora reactivity and the adaptive potential of species under changing climate. Some hypotheses postulate diversification due to vegetation removal and important isolation in southern refugia (Tabula Rasa), while others explain phylogeographic patterns by the survival of species in favourable Nunataks within the Alps. Since numerous species have successfully reacted to past climate changes by genome multiplication (autopolyploidy), studies of such taxa in natural conditions is likely to explain the ecological success and the advantages of autopolyploidy. Early cytogeographical surveys of Biscutella laevigata have shed light on the links between autopolyploidy and glaciations by indicating that diploids are now spatially isolated in never-glaciated areas, while autotetraploids have recolonised the zones covered by glaciers- during the last glacial maximum. A periglacial context apparently favoured this young autopolyploid complex but the circumstances and the advantages of this genomic mutation remain unclear. What is the glacial history of the B. laevigata autopolyploid complex? Are there multiple events of polyploidisation? To what extent do they affect the genetic diversity and the evolutionary potential of polyploids? Is recolonisation associated with adaptive processes? How does long-term persistence affect genetic diversity? The present study addresses these questions at different spatiotemporal scales. A regional survey at the Western Alps-scale tackles distal factors (evolutionary history), while local-scale studies explore proximal factors (evolutionary mechanisms). In the Western Alps, populations have been densely sampled and studied from the (1) cytotypic, (2) morphotaxonomic, (3) habitat point of views, as well as (4) plastid DNA molecular markers, in order to infer their relationships and establish the maternal lineages phylogeography. At the local scale, populations persisting at the rear edge and populations recolonising the attitudinal margin at the leading edge have been studied by AFLPs to show how genetic diversity is shaped by different evolutionary forces across the species range. The results at the regional scale document the glacial history of a widespread species, representative of alpine meadows, in a regional area of main interest (glacial refugia, main barriers and recolonisation routes) and points out to sites of interest for regional biodiversity. The external Alps have played a major role in the maintenance of populations near the central Alps during the Last Glacial Maximum and influenced the evolution of the species, and of vegetation. Polytopic autopolyploidy in different biogeographic districts is also demonstrated. The species has had an important and rapid radiation because recolonisation took place from different refugia. The subsequent recolonisation of the Western Alps was achieved by independent lineages that are presently admixing in the central Alps. The role of the Pennic summit line is underlined as a great barrier that was permeable only through certain favourable high-altitude passes. The central Alps are thus viewed as an important crossroad where genomes with different evolutionary histories are meeting and admixing. The AFLP analysis and comparison of local populations growing in contrasted ecological and historical situations indicate that populations persisting in the external Alps present restricted gene dispersal and low genetic diversity but seem in equilibrium with their environment. On the contrary, populations colonising the attitudinal margin are mainly influenced by founder effects together with great gene dispersal and genotypes have a nearly random distribution, suggesting that recolonisation is not associated with adaptive processes. Autopolyploids that locally persist against climate changes thus seem to present adaptive ability, while those that actively recolonise the Alps are successful because of their great capacity to maintain a high genetic diversity against founder effects during recolonisation.